Parameter estimation for stochastic models of biochemical reactions

Parameter estimation is very important for the analysis of models in systems biology. Computational modeling is a central approach in systems biology, for studying increasingly complex biochemical systems. Progress in experimental techniques, e.g. the possibility to measure small numbers of molecules in single cells [1], highlights the need for stochastic modeling approaches. Simulation methods for stochastic processes are being developed for decades since [2], and nowadays exist with a lot of variants [3]. Parameter estimation methods for stochastic models, however, are still in the early phase of development.